Metaheuristic search algorithms due to their heuristic nature usually need tuning of parameters, components and/or strategies to achieve acceptable performance on a particular problem. While there has been much work on tools and techniques to address this Tuning Problem, there has been relatively little work which takes advantage of putting humans in the metaheuristic analysis/evaluation loop. This paper proposes the use of a search trajectory visualization tool, Viz, which is meant to make it easier for humans (e.g. the algorithm designer/programmer) to understand, evaluate and design metaheuristics for search. In particular, our visualization exploits the human's capabilities for finding patterns in search trajectory by using a combination of spatial visualizations. We use the Travelling Salesman Problem to illustrate how Viz can be used to visualize the behavior of two local search algorithms with different heuristics.